000 | 04366nam a22006135i 4500 | ||
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001 | 978-3-319-32545-3 | ||
003 | DE-He213 | ||
005 | 20220801221124.0 | ||
007 | cr nn 008mamaa | ||
008 | 160413s2016 sz | s |||| 0|eng d | ||
020 |
_a9783319325453 _9978-3-319-32545-3 |
||
024 | 7 |
_a10.1007/978-3-319-32545-3 _2doi |
|
050 | 4 | _aQ334-342 | |
050 | 4 | _aTA347.A78 | |
072 | 7 |
_aUYQ _2bicssc |
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_aCOM004000 _2bisacsh |
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072 | 7 |
_aUYQ _2thema |
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082 | 0 | 4 |
_a006.3 _223 |
100 | 1 |
_aZielesny, Achim. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _954241 |
|
245 | 1 | 0 |
_aFrom Curve Fitting to Machine Learning _h[electronic resource] : _bAn Illustrative Guide to Scientific Data Analysis and Computational Intelligence / _cby Achim Zielesny. |
250 | _a2nd ed. 2016. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2016. |
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300 |
_aXV, 498 p. 343 illus., 200 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aIntelligent Systems Reference Library, _x1868-4408 ; _v109 |
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505 | 0 | _aIntroduction -- Curve Fitting -- Clustering -- Machine Learning -- Discussion -- CIP -Computational Intelligence Packages. | |
520 | _aThis successful book provides in its second edition an interactive and illustrative guide from two-dimensional curve fitting to multidimensional clustering and machine learning with neural networks or support vector machines. Along the way topics like mathematical optimization or evolutionary algorithms are touched. All concepts and ideas are outlined in a clear cut manner with graphically depicted plausibility arguments and a little elementary mathematics. The major topics are extensively outlined with exploratory examples and applications. The primary goal is to be as illustrative as possible without hiding problems and pitfalls but to address them. The character of an illustrative cookbook is complemented with specific sections that address more fundamental questions like the relation between machine learning and human intelligence. All topics are completely demonstrated with the computing platform Mathematica and the Computational Intelligence Packages (CIP), a high-level function library developed with Mathematica's programming language on top of Mathematica's algorithms. CIP is open-source and the detailed code used throughout the book is freely accessible. The target readerships are students of (computer) science and engineering as well as scientific practitioners in industry and academia who deserve an illustrative introduction. Readers with programming skills may easily port or customize the provided code. "'From curve fitting to machine learning' is ... a useful book. ... It contains the basic formulas of curve fitting and related subjects and throws in, what is missing in so many books, the code to reproduce the results. All in all this is an interesting and useful book both for novice as well as expert readers. For the novice it is a good introductory book and the expert will appreciate the many examples and working code." Leslie A. Piegl (Review of the first edition, 2012). | ||
650 | 0 |
_aArtificial intelligence. _93407 |
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650 | 0 |
_aEngineering mathematics. _93254 |
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650 | 0 |
_aEngineering—Data processing. _931556 |
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650 | 0 |
_aData mining. _93907 |
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650 | 0 |
_aQuantitative research. _94633 |
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650 | 0 |
_aMathematical optimization. _94112 |
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650 | 1 | 4 |
_aArtificial Intelligence. _93407 |
650 | 2 | 4 |
_aMathematical and Computational Engineering Applications. _931559 |
650 | 2 | 4 |
_aData Mining and Knowledge Discovery. _954242 |
650 | 2 | 4 |
_aData Analysis and Big Data. _954243 |
650 | 2 | 4 |
_aOptimization. _954244 |
710 | 2 |
_aSpringerLink (Online service) _954245 |
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773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783319325446 |
776 | 0 | 8 |
_iPrinted edition: _z9783319325460 |
776 | 0 | 8 |
_iPrinted edition: _z9783319813134 |
830 | 0 |
_aIntelligent Systems Reference Library, _x1868-4408 ; _v109 _954246 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-319-32545-3 |
912 | _aZDB-2-ENG | ||
912 | _aZDB-2-SXE | ||
942 | _cEBK | ||
999 |
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